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    • 1. 发明授权
    • Detecting objects in images using image gradients
    • 使用图像梯度检测图像中的对象
    • US08763908B1
    • 2014-07-01
    • US13431864
    • 2012-03-27
    • Bryan E. FeldmanArnab S. DhuaNalin Pradeep Senthamil
    • Bryan E. FeldmanArnab S. DhuaNalin Pradeep Senthamil
    • G06K7/10
    • G06K7/1443
    • The present technology relates to methods, systems and computer program products for detecting objects in images captured by a camera of a mobile device. The detection of objects (such as barcodes, QR codes, and text) in images can be based at least in part on image gradients of the image. The image can be divided into a plurality of regions, each having a dominant gradient direction. Based at least in part on the dominant gradient directions of the regions satisfying orientation thresholds, the regions can be identified as candidate or non-candidate regions for corresponding to a predetermined object. The candidate regions can be merged if they satisfy a connecting criterion. The merged regions can then be analyzed to determine if the merged regions satisfy a geometric property of the predetermined object, such as having a rectangular shape substantially similar to that of a barcode.
    • 本技术涉及用于检测由移动设备的相机捕获的图像中的对象的方法,系统和计算机程序产品。 图像中对象(如条形码,QR码和文本)的检测至少部分可以基于图像的图像梯度。 图像可以被分成多个区域,每个区域具有主要梯度方向。 至少部分地基于满足定向阈值的区域的主要梯度方向,可以将区域识别为对应于预定对象的候选或非候选区域。 候选区域如果满足连接标准,则可以合并。 然后可以分析合并的区域以确定合并区域是否满足预定对象的几何属性,诸如具有与条形码基本相似的矩形形状。